All comparisons

GPT-5.5 vs Gemini 3 Pro: Frontier Reasoning Compared in 2026

OpenAI's GPT-5.5 and Google's Gemini 3 Pro Preview are 2026's two non-Anthropic flagships. Both are frontier reasoning models. Both shipped vision and audio. The differences come down to philosophy: OpenAI bets on broadest knowledge + tightest reasoning; Google bets on biggest context + native multimodal.

Option A

GPT-5.5

OpenAI

Frontier reasoning, native multimodal, 256k context.

Context
256k
Max output
32k
Input/M (official)
$4.00
Output/M (official)
$32.00
Strengths
  • +Strongest pure reasoning on math, science, novel problems
  • +Broadest world knowledge — better at obscure facts
  • +Native multimodal: vision, audio, image generation
  • +Mature streaming + tool calling
  • +Strong code reasoning (also see GPT-5.3 Codex)
Weaknesses
  • −32k max output is restrictive for long-form work
  • −$32/M output is the most expensive in any flagship
  • −Smaller context vs Gemini's 1M
  • −Tool-call output drifts more than Claude in long chains
Option B

Gemini 3 Pro Preview

Google

1M context, best multimodal vision, default thinking mode.

Context
1,000k (1M)
Max output
65k
Input/M (official)
$4.80
Output/M (official)
$28.80
Strengths
  • +1M token context — load entire codebases, long docs, full transcripts
  • +Best-in-class vision accuracy
  • +Native multimodal including video understanding
  • +Default thinking mode improves reasoning on hard prompts
  • +Cheaper output than GPT-5.5 ($28.80 vs $32)
Weaknesses
  • −Default thinking consumes output tokens (set max_tokens >= 1000)
  • −Tool-call format less consistent
  • −Streaming + advanced tool-use less mature on third-party endpoints
  • −$4.80 input slightly more expensive than GPT-5.5 ($4)

Round-by-round

Hard pure reasoning

Winner: GPT-5.5

GPT-5.5 leads on math olympiad, novel scientific reasoning, hard puzzles. Gemini 3 Pro is competitive but GPT-5.5 has the edge.

Long-document analysis

Winner: Gemini 3 Pro Preview

1M context vs 256k. For really long docs (legal contracts, full books, multi-hour transcripts), Gemini handles in one prompt. GPT requires chunking.

Multimodal vision

Winner: Gemini 3 Pro Preview

Gemini 3 Pro's vision is more accurate. GPT-5.5 vision works well but Gemini's native multimodal training shows.

Code generation (one-shot)

Winner: GPT-5.5

GPT-5.5 (and especially GPT-5.3 Codex) edges Gemini on hard coding tasks. Gemini can write code but GPT's training on code-heavy data shows.

Long-form generation

Winner: Gemini 3 Pro Preview

65k max output beats 32k. For full reports, long content, complete code files — Gemini has more headroom.

Tool calling for agents

Winner: GPT-5.5

GPT-5.5 tool-call format is more consistent than Gemini's. For agent frameworks, GPT-5.5 has fewer error-recovery hacks.

Final verdict

GPT-5.5 for hard reasoning, novel problems, code, and agent loops. Gemini 3 Pro for very-long-context analysis, multimodal-heavy tasks, and long-form generation. Smart pattern: Gemini for the input pipeline (large doc → analysis), GPT-5.5 for the output decision. Both 80% off through claudeapi.cheap with one key.

The cheapest path to either winner

claudeapi.cheap exposes both at 80% off. GPT-5.5 = $0.80 input / $6.40 output per 1M (Pro). Gemini 3 Pro = $0.96 input / $5.76 output per 1M. Use the OpenAI SDK pointed at our /v1/chat/completions for both — model id is gpt-5.5 or gemini-3-pro-preview.

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FAQ

Can Gemini 3 Pro really use 1M tokens?

Yes, in practice. Recall is good up to ~700k. Past that, attention drops. For most workloads (loading a whole codebase, a long PDF), 1M context is real and usable.

Why does Gemini default to thinking mode?

Google decided always-on chain-of-thought improves baseline answer quality. The downside: thinking eats output tokens silently before the visible answer. claudeapi.cheap auto-floors max_tokens at 1000 for Gemini Pro models so you don't get empty responses.

Is GPT-5.3 Codex a better choice than GPT-5.5 for code?

For pure code generation, yes — Codex is fine-tuned for software engineering at $1.40/$11.20 vs GPT-5.5's $4/$32. For tasks mixing code + general reasoning, GPT-5.5 is more flexible.

Through claudeapi.cheap, are they both fully supported?

GPT-5.5 has full support: streaming, tools, multimodal. Gemini 3 Pro is currently text-only non-streaming on our path; streaming + tools + vision are on the roadmap.